nanoresearch
Minimal autonomous ML research: scout ideas, run experiments, write papers.
Pacote de plugins · de chrisliu298
Resumo
nanoresearch é um pacote de plugins para ferramentas de programação com IA publicado por chrisliu298. Marketplaces que lemos e que o listam: 1 (Community GitHub marketplaces). Vimos pela primeira vez em 2026-10-14 e não registramos mudanças desde então. Conforme nossa passagem pelos marketplaces em 2026-10-15.
O que pede
- Instala-se como pacote de plugins
Nenhum dos marketplaces que lemos publica as ferramentas ou as configurações que ele pede.
O que declara, pede e executa, por completo
Instale apenas plugins de desenvolvedores em quem você confia. Mostramos o que os marketplaces publicam e não testamos plugins.
Funciona com
- Claude Code
Pelos marketplaces que o listam e pelo transporte MCP que declara, conforme cada cliente documenta. Não testamos plugins.
Conectar
Comandos e configurações gerados apenas a partir do que os marketplaces declaram. Não os executamos por você e não testamos plugins.
Como plugin do Claude Code
Gerado a partir do que Community GitHub marketplaces declara.
/plugin marketplace add chrisliu298/nanoresearch
/plugin install nanoresearch@nanoresearchOnde está publicado
| Marketplace | Status | Versão | Números | Verificado | Visto pela primeira vez |
|---|---|---|---|---|---|
| Marketplace da comunidade chrisliu298/nanoresearch (Abrir o código no GitHub) | Não visto na última passagem | 0.1.0 | Forks (GitHub): 0 Estrelas (GitHub): 2 |
Sem marcação |
Cada número é do próprio marketplace e nunca é somado entre marketplaces. Um marketplace que não publica números não mostra nenhum: sem número não é zero.
Listado em um marketplace da comunidade
| Marketplace | Repositório | Estrelas (GitHub) |
|---|---|---|
| nanoresearch | chrisliu298/nanoresearch | 2 |
O que o pacote contém
Conforme publicado em Community GitHub marketplaces.
Comandos: 5
loopnanoresearchreviewscoutwrite
Agentes: 3
area-chairreviewerwrite-critic
O que mudou
- Passou a ser um produto que acompanhamos
- Community GitHub marketplaces: apareceu
Plugins semelhantes
Produtos cujos próprios nomes, descrições, ferramentas e skills são os mais próximos deste pelo significado, em todos os marketplaces que lemos. A proximidade é ordenada apenas dentro desta lista.
-
Automated AI research toolkit: hypothesis generation, experiments, and paper writing
-
Autonomous experiment loops on any codebase — one file, one metric, one loop. An agent edits a constrained file, runs an eval, keeps improvements, reverts failures, and repeats…
-
Multi-agent deep research pipelines for Claude Code. Runs internet research, repository analysis, schema-driven structured research, and media research (via NotebookLM) using…
-
openpaper-mcp io.github.federicodeponte/openpaper-mcp
Autonomous research engine: auto research from a prompt to a fully-cited academic paper via MCP
-
Research sprint orchestrator for Claude Code. Ask a question, get a decision-ready brief — every finding is tracked as a typed claim, adversarially challenged, confidence-graded…
-
Recursive research up to PhD level across any domain (science, tech, business, arts, humanities). Source tiering, WDM + Munger inversion for autonomous decisions, and disk…
-
Physics research around a research.md backbone: one research cycle, investigation, verification, writing, learning, brainstorming and method distillation.
-
Agent skills for research: autonomous iteration loops, bibliography management, data visualization, scientific coding, image generation, and TTS.
-
Three AI models, one synthesis — multi-model research workflow for scientific domains
Plugins semelhantes por marketplace
A mesma pergunta feita a cada marketplace separadamente: existe lá um equivalente deste plugin?
Listado em Claude Code: claude-plugins-community (5)
-
Autonomous experiment loops on any codebase — one file, one metric, one loop. An agent edits a constrained file, runs an eval, keeps improvements, reverts failures, and repeats…
-
Multi-agent deep research pipelines for Claude Code. Runs internet research, repository analysis, schema-driven structured research, and media research (via NotebookLM) using…
-
Research sprint orchestrator for Claude Code. Ask a question, get a decision-ready brief — every finding is tracked as a typed claim, adversarially challenged, confidence-graded…
-
20 enterprise-grade skills for autonomous AI/ML research lab operations. Includes 10 custom gap-analysis skills (research-commander, agent-debugger, model-evaluator…
-
Autonomous skill improvement through parallel research agents. Inspired by Karpathy's autoresearch methodology, it spawns 5 parallel agents (domain expert, quality auditor…
Listado em Claude Code: claude-plugins-official (5)
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
Full Domino Data Lab platform support — workspaces, jobs, model deployment, experiment tracking, GenAI tracing, Spark/Ray/Dask, and app deployment for data science teams
-
Build, train, evaluate, and use open source AI models, datasets, and spaces.
-
Build high-quality datasets and computer vision models. Visualize datasets, analyze models, find duplicates, run inference, evaluate predictions, and develop custom plugins.
-
Interactive self-referential AI loops for iterative development, implementing the Ralph Wiggum technique. Claude works on the same task repeatedly, seeing its previous work, until…
Listado em Claude: knowledge-work-plugins (5)
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
Connect to preclinical research tools and databases (literature search, genomics analysis, target prioritization) to accelerate early-stage life sciences R&D
-
AI-first project auditor and re-engineer based on the 9 design principles and 7 design patterns from the TechWolf AI-First Bootcamp
-
Build multimodal AI applications with Pixeltable -- tables, computed columns, embedding search, UDFs, tool-calling agents, and 25+ AI provider integrations.
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
Listado em Codex: openai-curated (openai/plugins) (5)
-
Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces…
-
Consensus is the go-to MCP for academic research. Connect directly to 220M+ peer-reviewed papers to search, synthesize, and build structured research outputs from within your…
-
Evaluate Codex skills and plugins from chat with a beginner-friendly start command, local-first reports, token budget explanations, and guided benchmarking.
-
Work with Zotero from Codex: search your library, export BibTeX, insert citations, and import references through the Zotero desktop app.
-
An agentic skills framework & software development methodology that works: planning, TDD, debugging, and collaboration workflows.
Listado em Community GitHub marketplaces (4)
-
Automated AI research toolkit: hypothesis generation, experiments, and paper writing
-
Autonomous experiment loops on any codebase — one file, one metric, one loop. An agent edits a constrained file, runs an eval, keeps improvements, reverts failures, and repeats…
-
Recursive research up to PhD level across any domain (science, tech, business, arts, humanities). Source tiering, WDM + Munger inversion for autonomous decisions, and disk…
-
Physics research around a research.md backbone: one research cycle, investigation, verification, writing, learning, brainstorming and method distillation.
Listado em Copilot CLI: github/awesome-copilot (5)
-
Run a lightweight, role-separated AI development team with flexible tools, developer-selected models, proportionate planning, and optional QA.
-
Goal-driven task orchestration with independent verification. Interviews the user to define a clear goal, then loops between a Builder subagent (does the work) and an Inspector…
-
Create, edit, run, save, and checkpoint Jupyter notebooks in an interactive Copilot canvas.
-
Task Researcher and Task Planner for intermediate to expert users and large codebases - Brought to you by microsoft/edge-ai
-
Model, visualize, and deploy applications with Radius from the GitHub Copilot app and CLI.
Listado em Copilot CLI: github/copilot-plugins (5)
-
Toolkit for building Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, and capability configuration.
-
Bring Azure DevOps work-item, repository, and pull-request workflows into GitHub Copilot.
-
Build Power Apps Canvas Apps using the Canvas Authoring MCP server.
-
model-apps
Build and deploy Power Apps generative pages for model-driven apps with specialist agents for planning, entity creation, and parallel code generation. Requires PAC CLI >= 2.7.0…
-
mcp-apps
Generate MCP App widgets for MCP tools. Produces self-contained HTML widgets using the MCP Apps protocol.
Listado em Cursor: cursor/plugins (5)
-
Consult a stronger model before major decisions, when stuck, and before declaring done.
-
Iterative self-referential AI loops using the Ralph Wiggum technique.
-
Generate presentations, documents, and webpages.
-
if you want to go fast, go deep first. pstack helps you write less, but higher quality code. rigorous agent workflows you can parallelize with confidence.
-
Fan large tasks out across parallel cloud agents with planners, workers, verifiers, and structured handoffs.
Listado em Docker MCP Catalog (5)
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
Tools for interacting with Hugging Face models, datasets, research papers, and more.
-
Real-time web search, reasoning, and research through Perplexity's API
-
Sequential Thinking (Reference)
Dynamic and reflective problem-solving through thought sequences.
-
Production-ready RAG service to search and retrieve data from your documents.
Listado em Official MCP Registry (5)
-
Automated AI research toolkit: hypothesis generation, experiments, and paper writing
-
openpaper-mcp io.github.federicodeponte/openpaper-mcp
Autonomous research engine: auto research from a prompt to a fully-cited academic paper via MCP
-
Read-only MCP over the LivingMeta AI-in-Research corpus: 12,400 papers, gaps, priority agenda.
-
agentcite io.github.Kevinx702/agentcite
Fabrication-free, DOI-backed citations for AI agents — real openAlex sources, never hallucinated.
-
Finds what shipped after your coding agent's training, before it rebuilds it from scratch.
Encontrados pelo significado, não por código ou repositório em comum: plugins semelhantes continuam sendo produtos distintos, e isto não é uma avaliação nem uma recomendação.
Quer esta marca no seu plugin em nosso catálogo?
Prove que o mantém com um arquivo no repositório, um arquivo no seu domínio ou um registro DNS, e você poderá mostrar esta marca na ficha, com banners ao vivo para o seu site e o README. Como funciona a verificação
Você também recebe alertas quando um marketplace o publica, o remove, muda a marca de verificado ou o que ele pede, e o endpoint remoto passa a ser monitorado como um serviço web.
Dados de Community GitHub marketplaces. Os números vêm das nossas próprias passagens regulares pelos marketplaces, última leitura em . Não publicamos dados de contato dos editores de plugins.